Tan, Ming T.

Bayesian missing data problems: EM, data augmentation and noniterative computation - Boca Raton CRC Press 2010 - xviii, 328 p - Chapman & Hall/CRC biostatistics series; 32 .

Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors. The methods are based on the inverse Bayes formulae discovered by one of the author in 1995. Applying the Bayesian approach to important real-world problems, the authors focus on exact numerical solutions, a conditional sampling approach via data augmentation, and a noniterative sampling approach via EM-type algorithms. (http://www.crcpress.com/product/isbn/9781420077490)


Bayesian statistical decision theory
Missing observations (Statistics)

519.542 / T2B2

Powered by Koha